Structure-activity relationships based on 3D-QSAR CoMFA/CoMSIA and design of aryloxypropanol-amine agonists with selectivity for the human β3-adrenergic receptor and anti-obesity and anti-diabetic profiles

Indexación: Scopus.Acknowledgments: This work was supported by FONDECYT No. 11130701. We would also like to thank fDoTr CthLeafbr efeora vthaeil afrbeilei tayvoafiltahbeilsitoyf towfa trheer seoqfutwireadret orecqaulciureladt etothcealAcuDla(thet ttph:e/ A/dDt c(lhatbt.pw:/e/dbstc.cloabm.w/seobfst.wcoamre/-stoofotlws aarned-tools and http://teqip.jdvu.ac.in/QSAR_Tools/). SDG. Conflicts of Interest: The authors declare no conflict of interest. Conflicts of Interest: The authors declare no conflict of interest.The wide tissue distribution of the adrenergic β3 receptor makes it a potential target for the treatment of multiple pathologies such as diabetes, obesity, depression, overactive bladder (OAB), and cancer. Currently, there is only one drug on the market, mirabegron, approved for the treatment of OAB. In the present study, we have carried out an extensive structure-activity relationship analysis of a series of 41 aryloxypropanolamine compounds based on three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. This is the first combined comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) study in a series of selective aryloxypropanolamines displaying anti-diabetes and anti-obesity pharmacological profiles. The best CoMFA and CoMSIA models presented values of r2 ncv = 0.993 and 0.984 and values of r2 test = 0.865 and 0.918, respectively. The results obtained were subjected to extensive external validation (q2, r2, r2 m, etc.) and a final series of compounds was designed and their biological activity was predicted (best pEC50 = 8.561). © 2018 by the authors.https://www.mdpi.com/1420-3049/23/5/119

Evaluating the performance of model transformation styles in Maude

Rule-based programming has been shown to be very successful in many application areas. Two prominent examples are the specification of model transformations in model driven development approaches and the definition of structured operational semantics of formal languages. General rewriting frameworks such as Maude are flexible enough to allow the programmer to adopt and mix various rule styles. The choice between styles can be biased by the programmer’s background. For instance, experts in visual formalisms might prefer graph-rewriting styles, while experts in semantics might prefer structurally inductive rules. This paper evaluates the performance of different rule styles on a significant benchmark taken from the literature on model transformation. Depending on the actual transformation being carried out, our results show that different rule styles can offer drastically different performances. We point out the situations from which each rule style benefits to offer a valuable set of hints for choosing one style over the other

Synthesis and characterization of graphene/polythiophene (GR/PT) nanocomposites:Evaluation as high-performance supercapacitor electrodes

Composites of polythiophene (PT) and graphene (GR) with different mass proportions were studied for their application as supercapacitors. Fourier transform infrared spectroscopy (FTIR) along with High Resolution Scanning electron microscopy (HR-SEM) were employed in order to characterize the morphology and composition of the resulting composites. The electrochemical behaviour of these composites was studied by means of cyclic voltammetry and specific capacitance curves were derived from these measurements. The Faradaic impedance spectroscopy response of the different composites, along with that of GR, was also studied. From these measurements it was found that a 1:1 in mass composite of GR and PT showed a higher specific capacitance, even when compared with GR alone. The introduction of the GR in that proportion also showed an enhanced cyclic stability in comparison with the sole polymer. The high specific capacitance (365 F g-1 at 1 A g-1) of this composite material indicates its potential for use as an electrode material for supercapacitors.Fil: Melo, J. P.. Universidad Bernardo OHiggins; ChileFil: Schulz, Eduardo Nicolás. Universidad Nacional del Sur. Departamento de Ingeniería Química. Instituto de Ingeniería Electroquímica y Corrosión; Argentina. University of Birmingham; Reino UnidoFil: Morales Verdejo, C.. Universidad Bernardo OHiggins; ChileFil: Horswell, S. L.. University of Birmingham; Reino UnidoFil: Camarada, M. B.. Universidad Bernardo OHiggins; Chil

Investigating the Mechanisms of Hallucinogen-Induced Visions Using 3,4-Methylenedioxyamphetamine (MDA): A Randomized Controlled Trial in Humans

The mechanisms of drug-induced visions are poorly understood. Very few serotonergic hallucinogens have been studied in humans in decades, despite widespread use of these drugs and potential relevance of their mechanisms to hallucinations occurring in psychiatric and neurological disorders.We investigated the mechanisms of hallucinogen-induced visions by measuring the visual and perceptual effects of the hallucinogenic serotonin 5-HT2AR receptor agonist and monoamine releaser, 3,4-methylenedioxyamphetamine (MDA), in a double-blind placebo-controlled study. We found that MDA increased self-report measures of mystical-type experience and other hallucinogen-like effects, including reported visual alterations. MDA produced a significant increase in closed-eye visions (CEVs), with considerable individual variation. Magnitude of CEVs after MDA was associated with lower performance on measures of contour integration and object recognition.Drug-induced visions may have greater intensity in people with poor sensory or perceptual processing, suggesting common mechanisms with other hallucinatory syndromes. MDA is a potential tool to investigate mystical experiences and visual perception

Rewriting Logic Semantics of a Plan Execution Language

The Plan Execution Interchange Language (PLEXIL) is a synchronous language developed by NASA to support autonomous spacecraft operations. In this paper, we propose a rewriting logic semantics of PLEXIL in Maude, a high-performance logical engine. The rewriting logic semantics is by itself a formal interpreter of the language and can be used as a semantic benchmark for the implementation of PLEXIL executives. The implementation in Maude has the additional benefit of making available to PLEXIL designers and developers all the formal analysis and verification tools provided by Maude. The formalization of the PLEXIL semantics in rewriting logic poses an interesting challenge due to the synchronous nature of the language and the prioritized rules defining its semantics. To overcome this difficulty, we propose a general procedure for simulating synchronous set relations in rewriting logic that is sound and, for deterministic relations, complete. We also report on two issues at the design level of the original PLEXIL semantics that were identified with the help of the executable specification in Maude

Effects of ecstasy/polydrug use on memory for associative information

Rationale Associative learning underpins behaviours that are fundamental to the everyday functioning of the individual. Evidence pointing to learning deficits in recreational drug users merits further examination. Objectives A word pair learning task was administered to examine associative learning processes in ecstasy/polydrug users. Methods After assignment to either single or divided attention conditions, 44 ecstasy/polydrug users and 48 non-users were presented with 80 word pairs at encoding. Following this, four types of stimuli were presented at the recognition phase: the words as originally paired (old pairs), previously presented words in different pairings (conjunction pairs), old words paired with new words, and pairs of new words (not presented previously). The task was to identify which of the stimuli were intact old pairs. Results Ecstasy/ploydrug users produced significantly more false-positive responses overall compared to non-users. Increased long-term frequency of ecstasy use was positively associated with the propensity to produce false-positive responses. It was also associated with a more liberal signal detection theory decision criterion value. Measures of long term and recent cannabis use were also associated with these same word pair learning outcome measures. Conjunction word pairs, irrespective of drug use, generated the highest level of false-positive responses and significantly more false-positive responses were made in the divided attention condition compared to the single attention condition. Conclusions Overall, the results suggest that long-term ecstasy exposure may induce a deficit in associative learning and this may be in part a consequence of users adopting a more liberal decision criterion value

Comments on Marine Litter in Oceans, Seas and Beaches: Characteristics and Impacts.

Marine litter is observed along shorelines, pelagic, benthic marine and lake systems all around the globe. On beaches, litter creates aesthetic and related economic problems because a clean beach is one of the most important characteristics of a seaside resort required by visitors. Litter can reach the marine environment from marine or land activities but it is estimated that 80% originates from land-based sources. The marine-based sources of litter include all types of sea-going vessel and offshore installations, the most abundant plastic debris in the oceans being derelict (lost or improperly discarded) fishing gear. Most of marine litter is composed by plastics due to their greater durability and persistence, combined with plastic rising production and low rates of recovery. Special importance is linked to microplastics because their ubiquity, persistence, mechanical effects on biota and the ecosystem because of ingestion by organisms and their toxic potential. As plastics degrade they can release toxic chemicals initially incorporated during their manufacturing or persistent organic pollutants and heavy metals sorbed to their surfaces in the environment. Such toxins can disrupt endocrine functions and cause harmful reproductive and developmental effects in aquatic animals

Seasonality of Tylenchulus semipenetrans Cobb and Pasteuria sp in citrus orchards in Spain

Population densities of the Mediterranean biotype of Tylenchulus semipenetrans were monitored in soil and citrus roots at 3-month intervals for 3 consecutive years in four citrus orchards in the provinces of Tarragona (Amposta and Xalamera) and Valencia (Moncada and Carcer). Nematode population densities in soil peaked once year in April or July depending on the orchard and year. Numbers of females per gram of root increased once or twice each year. The maximum density of eggs per gram of root was recorded in April at Xalamera and Carcer orchards, but there was no recognizable peak in the other two orchards. Numbers of nematodes in soil, females or eggs program of root, of eggs per female were correlated with either temperature or rainfall in the sampling month, 1 month before sampling, or in the second preceding month, depending on the orchard. Members of the Pasteuria group were present in the four citrus orchards, and a positive relationship occurred between nematodes in soil and bacterial parasitism (r(2) = 0.75) in the orchard at Amposta

Evaluation of dimensionality reduction methods applied to numerical weather models for solar radiation forecasting

The interest in solar radiation prediction has increased greatly in recent times among the scientific community. In this context, Machine Learning techniques have shown their ability to learn accurate prediction models. The aim of this paper is to go one step further and automatically achieve interpretability during the learning process by performing dimensionality reduction on the input variables. To this end, three non standard multivariate feature selection approaches are applied, based on the adaptation of strong learning algorithms to the feature selection task, as well as a battery of classic dimensionality reduction models. The goal is to obtain robust sets of features that not only improve prediction accuracy but also provide more interpretable and consistent results. Real data from the Weather Research and Forecasting model, which produces a very large number of variables, is used as the input. As is to be expected, the results prove that dimensionality reduction in general is a useful tool for improving performance, as well as easing the interpretability of the results. In fact, the proposed non standard methods offer important accuracy improvements and one of them provides with an intuitive and reduced selection of features and mesoscale nodes (around 10% of the initial variables centered on three specific nodes).This work has been partially supported by the projects TIN2014-54583-C2-2-R, TEC2014-52289-R and TEC2016-81900-REDT of the Spanish Interministerial Commission of Science and Technology (MICYT), and by Comunidad Autónoma de Madrid, under project PRICAM P2013ICE-2933

BOOTES-IR: Near IR follow-up GRB observations by a robotic system

“BOOTES-IR” is the extension of the BOOTES experiment, which operates in Southern Spain since 1998, to the near IR (NIR). The goal is to follow up the early stage of the gamma ray burst (GRB) afterglow emission in the NIR, alike BOOTES does already at optical wavelengths. The scientific case that drives the BOOTES-IR performance is the study of GRBs with the support of spacecraft like INTEGRAL, SWIFT and GLAST. Given that the afterglow emission in both, the NIR and the optical, in the instances immediately following a GRB, is extremely bright (reached V = 8.9 in one case), it should be possible to detect this prompt emission at NIR wavelengths too. The combined observations by BOOTES-IR and BOOTES-1 and BOOTES-2 will allow for real time identification of trustworthy candidates to have a high redshift (z > 5). It is expected that, few minutes after a GRB, the IR magnitudes be H ∼ 7–10, hence very high quality spectra can be obtained for objects as far as z = 10 by larger instruments